How to Choose the Right Type of Virtual Agent
After more than 10 years of working with contact center and customer service software solutions, I recently started a new career as a consultant. One of my first projects was to develop a buyer’s guide for virtual agents. Having spent the last three years working on automated self-service applications, I was thrilled to undertake the project. I've seen first-hand how intelligent virtual agents can provide businesses with tremendous value and are poised for growing market adoption.
This post offers a summary of the guide. I’ve also included my decision framework that helps buyers select the right type of virtual agent based on business need. You can find the full guide here.
Virtual agents, also known as virtual customer assistants, are software programs that can emulate human customer service or sales personnel, often based on artificial intelligence (AI) platforms. Virtual agents use either a speech (spoken) or chat (written) interface to “talk” to customers. Virtual agents automate repetitive tasks and transactions like allowing a customer to check balances, pay bills, authorize a credit card, or schedule an appointment. This allows your most valuable asset -- your people -- to focus on solving more complicated problems, saving you money while improving your customer’s experience.
Major advancements in AI, speech recognition, and natural language processing have given organizations that need to automate self-service a giant leap forward. For the first time ever, companies of all sizes can now use virtual agents to reduce costs and improve the customer experience.
The Rise of Virtual Agents -- Why Now?
Virtual agents often work closely with your human employees, offloading repetitive tasks. The technology has been around for over a decade but is just now exploding. What’s driving the current popularity?
- Rising Customer Expectations -- Today’s customers demand personalized answers fast, on demand, and delivered in a way that is most convenient to them. If you don’t meet their high expectations, they may turn to your competition that delivers a better experience.
- Demand for Self-Service -- More and more, customers now prefer self-service; in fact, Gartner predicts that by 2020, customers will manage 85% of their relationships with enterprises without interacting with humans. While this may be an ambitious forecast, it highlights an important trend that will continue as the millennial generation’s buying power grows.
- Technology Improvements and Growing Comfort with Conversational AI -- Consumers are now conversing daily with AI-based assistants, such as Amazon Alexa, Apple’s Siri, Microsoft Cortana, and Google Home. As they get comfortable with voice interfaces, they’re expecting to use similar technology in other areas. At the same time, AI technology and speech recognition capabilities are rapidly improving, leading to wider adoption of virtual agent technologies.
- Massive Focus on Digital Transformation -- Startup companies are using new technology-centric business strategies to disrupt legacy markets. The taxi business is facing competition from Uber and Lyft, and brick-and-mortar retailers are under pressure from Amazon. Even banking is facing competition from new digital-first lenders. Almost every segment of the market is facing new competition, and companies are racing to develop new digital business models to defend their businesses. Improving automated self-service is a key pillar of many organizations’ strategies to improve the customer experience and build more direct relationships with customers.
Chatbots & Speech-Enabled IVR Unite
Two types of self-service technologies are merging to become what we now call intelligent virtual agents.
The first started by offering self-service to customers over the phone in the form of IVR, eventually adding on basic speech recognition. The second, now called chatbots, later emerged to provide self-service through chat or SMS. Both types have become more intelligent over time, incorporating technologies like natural language processing (NLP) and machine learning (ML) to improve the quality and scope of service. We've now reached the point where an automated service solution can be designed once to support both voice and text-based channels of service, further reducing deployment costs.
Click below to Page 2: What Can a Virtual Agent Actually Do for Your Business?